A Novel Risk Model Based on Lipid Metabolism-Associated Genes Predicts Prognosis and Indicates Immune Microenvironment in Breast Cancer - Ye, Zhimin; Zou, Shengmei; Niu, Zhiyuan; Xu, Zhijie; Hu, Yongbin (Frontiers in Cell and Developmental Biology, 2021)
Abstract Background: Lipid metabolism were demonstrated to be involved in tumorigenesis and development of multiple cancers. While the role of lipid metabolism-associated genes (LMAGs) in immune microenvironment and prognosis in breast cancer (BRCA) remained rarely elucidated. Methods: 1076 BRCA patients were extracted from The Cancer Genome Atlas (TCGA) database and randomly assigned as training cohort (n = 760) and validation cohort (n = 316) in this study. Kaplan–Meier analysis was applied to assess the difference in survival. Consensus clustering was performed to categorize the BRCA patients into subtypes. LMAG-based prognostic risk model was constructed in the training cohort using multivariate Cox regression analysis, and validated in the validation cohort. Immune microenvironment was evaluated using ESTIMATE algorithm, TIMER algorithm, CIBERSORT and ssGSEA analyses. Results: Consensus clustering classified the BRCA patients into two subgroups with significant different overall survival and immune microenvironment, and better prognosis was associated with high immune infiltration. Prognostic risk model based on four LMAGs stratified the BRCA patients into high risk and low risk groups in both training and validation sets successfully, and high risk score predicted poor prognosis and indicated low immune status. Subgroup analysis suggested that the risk model was an independent predictor of prognosis in BRCA. Conclusion: To sum up, this study demonstrated that the expression of LMAGs played a crucial role in BRCA, and the LMAGs-based risk model predicted prognosis and indicated the immune microenvironment of BRCA patients.